SVM Based Method for Identification and Recognition of Faces by Using Feature Distances

In this paper, a scheme was presented to identify the locations of key features of a human face such as eyes, nose, chin known as the fiducial points and form a face graph. The relative distances between these features are calculated. These distance measures are considered to be unique identifying attributes of a person. The distance measures are used to train a Support Vector Machine (SVM). The identification takes place by matching the features of the presented person with the features that were used to train the SVM. The closest match results in identification. The Minimum Distance Classifier has been used to recognize a person uniquely using this SVM.